It sounds like you want to see what it’s like to work as a data engineer on Databricks.
No, I don’t want to become a better Data Engineer. I want to learn more about Python and prepare for the Databricks Certified Developer for Apache Spark 3.0 exam.
Then don’t look any further.
For example, this course will show you what a Data Engineering job is like so you can figure out if it’s the right job for you to do.
In less than an hour, thanks to a lot of practical examples, you will learn how to work with different types of data when you work with Databricks (comma-separated text files, XML files, tab-separated text files, fixed-width files).
During this course, you will learn how to use the Dataframe, Delta, Stream, and other APIs like a real Data Engineer.
The goal of this project is to get data from a wide range of file types and put it into Delta Tables for further analysis.
If you want to do this project on your own, it comes with all of the code you need to do it. You only need to run each cell of the notebooks.
At the very beginning of this project, you will be shown how a Data Engineer works every day.
The data is about global educational indicators, and it comes from data that the World Bank makes public. Please note that the author has changed some of the data for the sake of making the project easier. So, the data isn’t real data from the source, but it shows how to work with PySpark on Databricks (take it for demonstration purposes only).
It’s time to finish the project. To do this, you’ll answer some simple business questions based on the data you’ve already added.
Who this course is for:
- Anyone who wants to work as a Data Engineer on Databricks in the real world.
- Who wants to work as a Data Engineer with Databricks.
- Anyone who wants to put data into Delta Tables on Databricks.
- The Data Engineers who want to get the “Databricks Certified Developer for Spark 3.0” certification can go to this page to find out how to do that.